Modeling and simulation is standard practice in nearly every scientific field. Idaho National Laboratory’s Multiphysics Object
Oriented Simulation Environment (MOOSE) has transformed
approaches to predictive simulation, making it quick, adaptable
and more accessible. MOOSE is
a computer software that can be
loaded onto most UNIX-compli-ant operating systems including,
but not limited to, Mac OS X,
Ubuntu, OpenSuSE, Fedora,
CentOS and Redhat. It’s routinely deployed onto high-performance clusters
globally, but also runs without any modifications on standard laptop computers.

The software’s primary purpose is to solve complex models represented by partial
differential equations (PDEs). MOOSE is an object-oriented framework developed using quality-controlled modern software development practices. A rigorous
regression testing suite and rich documentation is included with the software. The
MOOSE framework consists of several consistently designed, pluggable interfaces
that scientists and engineers use to solve domain-specific problems. Internally,
MOOSE utilizes the finite element method (FEM) mathematical modeling technique due to its generality and wide applicability.

MOOSE enables development of simulation tools in a fraction of the time
previously required. A simulation effort requiring a team of 10 people working
for five years can be completed by three people in one year. The simplicity has
bred 40 different MOOSE-based modeling applications. The rapidly growing
MOOSE user community spans nuclear engineering, material science and geology and includes 45 domestic or foreign labs, universities and companies.

It solves the fundamental equations of mass, momentum, energy and chemical species transport using the finite element method (FEM), which can be
described by partial differential equations. The equations are made discrete for
solution on a digital computer with the FEM in space and the finite difference
method in time. The resulting nonlinear, time-dependent, algebraic equations
are solved with a full Newton-Raphson method. The linearized equations are
solved with direct or Krylov-based iterative solvers. The simulations can be run
on a single processor or on multiple processors in parallel using domain decomposition, which can greatly speed up engineering analysis.

Goma is designed as a general mechanics code, with no features that tie it
to any particular application. Problems to be solved are specified completely
in input files, which include code and material properties specifications. The
multitude of differential equations, material constitutive equations, and boundary conditions has evolved with the applications, but they are all from theories
published in the open literature and Goma’s theory manual.

◗ Sandia National Laboratories, www.sandia.gov

Fast Vacuum for Next-GenProcesses

The semiconductor industry is starting to adopt rapid
processes that require pressure values processed in as
little as 0.5 msec, yet produce low noise. This performance is needed to build chips that generate less heat,
run cooler and need less cooling resources.

Speed and noise improvements, available in

INFICON’s new Stripe CDG capacitive diaphragmgauge, fulfill the requirements of this next level ofstructure reduction in the process industry. StripeCDG delivers total vacuum pressure measurementsevery 0.33 msec. The pressure transformation runsat the same rate in the first step of data processing. Anewly developed filter algorithm combines variousseparate filter technologies and gives a noise opti-mized signal with a signal-to-noise ratio of higher than 10,000 at full scale. Thesecond step of data processing prepares for the digital output and the analog out-put. Thus, a new pressure value is available 0.33 msec after pressure change.

In lithography, polymer
“resists” are applied as a thin,
continuous layer over material that is to be patterned.

The resist is patterned, then
removed after the pattern
is duplicated on the silicon underneath. However,
smaller patterns demand
thinner resists, which can’t
survive plasma patterning.

Sequential Infiltration
Synthesis (SIS) Lithography, developed by Argonne National Laboratory and
implemented in industrial settings by several industry leaders, gives the resist
the ability to withstand plasma etching. It uses a sequence of gaseous chemical
exposures to infiltrate and infuse the polymer with tough ceramic materials.

This infusion, which is analogous to atomic layer deposition, is possible because
of chemical reactions between precursor vapors and functional groups on the
polymer backbone. During the initial stages of the process, “seeds” of the inorganic material are created that are bound to the polymer. Further reactions grow
the seeds larger, and the eventual product is a composite material comprised
of the organic polymer and the inorganic material that are intimately bound
together. The net result of this sequential infiltration synthesis is deeper, more
precise patterning of the substrate which can dramatically improve the performance of the resulting microelectronic circuitry.